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Biology subjects

Kaino, S.

Publications and source records attributed to Kaino, S..

2 recordsLinked to original sources

Novel frontier in wildlife monitoring: identification of small rodent species from faecal pellets using Near-Infrared Reflectance Spectroscopy (NIRS)

Small rodents are prevalent and functionally important across worlds biomes, making their monitoring salient for ecosystem management, conservation, forestry and agriculture. Yet, there is a dearth of cost-effective and non-invasive methods for large-scale, intensive sampling. As one such method, fecal pellet counts readily provide relative abundance indices. Given available analytical methods, feces could also allow for determination of multiple ecological and physiological variables, including community composition. We developed calibration models for rodent taxonomic determination using fecal near-infrared reflectance spectroscopy (fNIRS). Our results demonstrate fNIRS as an accurate and robust method for predicting genus and species identity of five co-existing subarctic microtine rodent species. We show that sample exposure to weathering did not reduce accuracy, indicating suitability of the method for samples collected from the field. Diet was not a major determinant of species prediction accuracy in our samples, as diet exhibited large variation and overlap between species. While regional calibration models predicted poorly samples from another region, calibration models including samples from two regions provided a good prediction accuracy for both regions. We propose fNIRS as a fast and cost-efficient high-throughoutput method for rodent taxonomic determination, and highlight its potential for cross-regional calibrations and use on field-collected samples. FNIRS can facilitate rodent population censuses at larger spatial extent than before deemed feasible, if combined with pellet-count based abundance indices. Given the versatility of fNIRS analytics, developing such monitoring schemes can support ecosystem- and interaction-based approaches to monitoring.

ecology↗

One leaf for all: Chemical traits of single leaves measured at the leaf surface using Near infrared-reflectance spectroscopy (NIRS)

O_LIThe leaf is an essential unit for measures of plant ecological traits. Yet, measures of plant chemical traits are often achieved by merging several leaves, masking potential foliar variation within and among plant individuals. This is also the case with cost-effective measures derived using Near-infrared reflectance spectroscopy (NIRS). The calibration models developed for converting NIRS spectral information to chemical traits are typically based on spectra from merged and milled leaves. In this study we ask if such calibration models can be applied to spectra derived from whole leaves, providing measures of chemical traits of single leaves. C_LIO_LIWe sampled cohorts of single leaves from different biogeographic regions, growth forms, species and phenological stages in order to include variation in leaf and chemical traits. For each cohort we first sampled NIRS-spectra from each whole, single leaf, including leaf sizes down to O 4 mm (the minimum area of our NIRS application). Next, we merged, milled and tableted the leaves and sampled spectra from the cohort as a tablet. We applied arctic-alpine calibration models to all spectra and derived chemical traits. Finally, we evaluated the performance of the models in predicting chemical traits of whole, single leaves by comparing the traits derived at the level of leaves to that of the tablets. C_LIO_LIWe found that the arctic-alpine calibration models can successfully be applied to single, whole leaves for measures of Nitrogen (R2=0.88, RMSE=0.824), Phosphorus (R2=0.65, RMSE=0.081), and Carbon (R2=0.78, RMSE=2.199) content. For Silicon content we found the method acceptable when applied to Silicon-rich growth forms (R2=0.67, RMSE=0.677). We found a considerable variation in chemical trait values among leaves within the cohorts. C_LIO_LIThis time- and cost-efficient NIRS-application provides non-destructive measures of a set of chemical traits in single, whole leaves, including leaves of small sizes. The application can facilitate research into the scales of variability of chemical traits and include intraindividual variation. Potential trade-offs among chemical traits and other traits within the leaf unit can be identified and be related to ecological processes. In sum this NIRS-application can facilitate further ecological understanding of the role of leaf chemical traits. C_LI

ecology↗